{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pylab import mpl\n",
    "# 设置显示中文字体\n",
    "mpl.rcParams[\"font.sans-serif\"] = [\"SimHei\"]\n",
    "# 设置正常显示符号\n",
    "mpl.rcParams[\"axes.unicode_minus\"] = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "def dxdt(F, X, t, h=1e-2):\n",
    "    assert(len(F)==len(X))\n",
    "    X = np.array(X)\n",
    "    K1 = np.array([f(X, t) for f in F])\n",
    "    dX = h*K1/2\n",
    "    K2 = np.array([f(X+dX, t+h/2) for f in F]) \n",
    "    dX = h*K2/2\n",
    "    K3 = np.array([f(X+dX, t+h/2) for f in F])\n",
    "    dX = h*K3 \n",
    "    K4 = np.array([f(X+dX, t+h) for f in F])\n",
    "    dX = (K1 + 2*K2 + 2*K3 + K4)*h/6\n",
    "    return dX, np.array([f(X, t) for f in F])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sat(x, delta):\n",
    "    return  x/delta if np.abs(x)<delta else np.sign(x)\n",
    "\n",
    "def fal(x, alpha=0.5, delta=0.1):\n",
    "    return  x/np.power(delta,1-alpha) if np.abs(x)<delta else np.power(np.abs(x), alpha)*np.sign(x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# target signal\n",
    "def v(t):\n",
    "    if t < 10:\n",
    "        return np.sign(np.sin(0.8*t))  \n",
    "    elif t < 20:\n",
    "        return 2*(0.5*t-int(0.5*t)-0.5)\n",
    "    else:\n",
    "        return np.sin(0.8*t)\n",
    "\n",
    "def v1(X, t):\n",
    "    x1, x2 = X[0], X[1]\n",
    "    return x2\n",
    "\n",
    "def v2(X, t):\n",
    "    x1, x2 = X[0], X[1]\n",
    "    return -R*sat(x1 - v(t) + np.abs(x2)*x2/(2*R), delta)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# eso\n",
    "# 极点配置\n",
    "p = np.poly1d([-15,-15,-15],True)\n",
    "_, b1, b2, b3 = tuple(p.coef)\n",
    "\n",
    "def g1(X, t):\n",
    "    x1,x2,x3 = X[0], X[1], X[2]    \n",
    "    return x2 - b1 * (x1 - y)  # y is model output\n",
    "\n",
    "def g2(X, t):\n",
    "    x1, x2, x3 = X[0], X[1], X[2]    \n",
    "    return x3 - b2 * (x1 - y) + u\n",
    "\n",
    "def g3(X, t):\n",
    "    x1, x2, x3 = X[0], X[1], X[2]    \n",
    "    return -b3 * (x1 - y)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# hidden uncertain model\n",
    "def f1(X, t):\n",
    "    x, y = X[0], X[1]    \n",
    "    return y\n",
    "\n",
    "def f2(X, t):\n",
    "    x, y = X[0], X[1]\n",
    "    return -x*x*x - x -0.2*y + w(t) + u\n",
    "\n",
    "def w(t):\n",
    "    return 0.2 * np.sign(np.cos(t))  # perturbation\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "R = 90  # params in sal\n",
    "delta = 0.001  # params in sal\n",
    "h = 0.01  # discrete time unit\n",
    "T = 20  # total time\n",
    "N = int(T/h)  # num of points\n",
    "V = [0., 0.]  # TD signal\n",
    "X = [0., 0.]  # true state\n",
    "Z = [0., 0., 0.]  # ESO \n",
    "u = 0  # initial control input\n",
    "\n",
    "actual_output = []\n",
    "expect_output = []\n",
    "uncertain_dynamics = []\n",
    "\n",
    "for i in range(N):\n",
    "    t = i*h  # time\n",
    "\n",
    "    dX, _ = dxdt([f1,f2],X,t,h)\n",
    "    X = X + dX\n",
    "    y = X[0]  # model output\n",
    "\n",
    "    dV, _ = dxdt([v1,v2],V,t,h)\n",
    "    V = V + dV\n",
    "\n",
    "    dZ, _ = dxdt([g1,g2,g3],Z,t,h)\n",
    "    Z = Z + dZ\n",
    "\n",
    "    e_p = V[0] - Z[0]\n",
    "    e_d = V[1] - Z[1]\n",
    "\n",
    "    fep, fed = fal(e_p), fal(e_d)\n",
    "\n",
    "    u = 10*fep + 50*fed - Z[2]\n",
    "\n",
    "    actual_output.append(y)\n",
    "    expect_output.append(V[0])\n",
    "    uncertain_dynamics.append(Z[2])\n",
    "\n",
    "\n",
    "plt.plot(actual_output, color='black', label='输出')\n",
    "plt.plot(expect_output, color='red', linestyle='--',label='预估值')\n",
    "plt.plot(uncertain_dynamics, color='green', linestyle='--',label='未知状态值')\n",
    "plt.legend(loc='lower right')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.0"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
